Using deep learning to improve contactless radio frequency sensing

A distinctive institutionWith a history dating back to 1821, Heriot-Watt University has established a reputation for world-class teaching and practical, leading-edge research, which has made us one of the top UK universities for business and industry.We're a vibrant, forward-looking university, well known for the quality of our degrees with employers actively seeking out our graduates.Heriot-Watt is also Scotland's most international university with an unsurpassed international in-country presence. We deliver degree programmes to 31,000 students globally, have campuses in Dubai and Malaysia and boast the largest international student cohort in Scotland.

Heriot-Watt University Dubai Campus

Explore wireless sensing using radio waves to create the next-gen wireless and mobile computing applications.

Heriot-Watt University Dubai

Recent years have seen deep learning applied successfully to radio-based sensing. Wi-Fi has evolved into both a communication and sensing platform due to its increasing PHY layer capabilities. In addition to sensing over Wi-Fi, simultaneous perception and communication would be possible without wearing sensor devices and, in the privacy-preserving case of contactless sensing, without additional communication infrastructure. The development of deep learning models in the last few years has led to the creation of large datasets and the exploration of a wide range of areas, as well as previously unknown situations and environments. The field of wireless sensing is still young, despite an increase in interest from the research community. In this talk, we will explore wireless sensing using radio waves to create next-generation wireless and mobile computing applications which enable spaces to become smart without adding any additional sensors.This session will be held both in person and online via Zoom.About the speaker Talal Shaikh is the Undergraduate Director of Studies at Heriot Watt University Dubai’s School of Mathematics and Computer Science (MACS). He teaches several courses including Intelligent Robotics, Software Engineering and Artificial Intelligence. His ongoing research covers Social Robotics, Computer Vision, Agriculture, Technology, Ubiquitous and Pervasive computing, Machine to Machine (M2M) technologies and the Internet of Things in the context of Smart Cities. His academic area of interest also covers student learning and student experience.With more than 10 years of experience, he is an industry veteran turned academician. Prior to this, he was the Chief Information Officer at a law firm where he managed multiple internal software development projects. He has also worked as a Software Engineer for an international company specializing in software solutions and consulting services for traffic and transportation, mobility and logistics. He is a member of the Association for Computing Machinery (ACM), the Institute of Electrical and Electronics Engineers (IEEE) as well as a Fellow of the Higher Education Academy (FHEA) in the UK. In his free time he volunteers to mentor teams for the Hackathon events. He also gives talks in schools to encourage and enlighten students about AI and Robotics technologies.-﻿-If you are unable to attend the event in person, join us for the online session on Zoom:https://us06web.zoom.us/j/85674049551See you there,

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Using deep learning to improve contactless radio frequency sensing

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Using deep learning to improve contactless radio frequency sensing

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